In the digital content publishing industry, it is desirable for a content publisher (e.g., a website provider) to present its users or readers not only with interesting, relevant, trustworthy and engaging content in an initial form (e.g., a webpage), but also provide users of the publisher's content with additional recommended content. Furthermore, it is a goal for a content publisher to provide its users with content in a manner which maximizes user engagement and consumption.
An aspect impacting a user's level of engagement with content on a webpage is the title of the content. A piece of digital content possesses and is usually linked to by a title, heading or headline. On many occasions, the wording or phrasing of the content title induces a high degree of interaction with the title/link (i.e., possesses a high user engagement with the title, such as a high Click Through Rate or CTR), but actual user engagement with the underlying content is low. This phenomenon is known in the content marketing industry as “clickbait” and can result in tricking the user to click on the content title in order to maximize the CTR, without any regard to the consequent user engagement with the underlying content. This practice can lead to the loss of user trust in the content publishing source and diminished overall content publisher revenue.
In addition, the reverse phenomenon is also prevalent, wherein content titles having low user engagement levels (e.g., a low CTR) are associated with underlying content that is highly engaging for the relatively few users that have clicked through to the content. In conventional digital publishing, a human editor managing the content of a web page is tasked with inefficiently associating a respective title with various content parameters. However, an automated approach is needed to determine optimal content titles to optimize both user engagement and user trust.